Showing 17 open source projects for "stochastic processes"

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  • 1
    NeuroMatch Academy (NMA)

    NeuroMatch Academy (NMA)

    NMA Computational Neuroscience course

    NMA Computational Neuroscience course. We have curated a curriculum that spans most areas of computational neuroscience (a hard task in an increasingly big field!). We will expose you to both theoretical modeling and more data-driven analyses. The Neuro Video Series is a series of 12 videos that covers basic neuroscience concepts and neuroscience methods. These videos are completely optional and do not need to be watched in a fixed order so you can pick and choose which videos will help you...
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  • 2
    DiffOpt.jl

    DiffOpt.jl

    Differentiating convex optimization programs w.r.t. program parameters

    ...With the help of automatic differentiation, differentiable optimization can have a significant impact on creating end-to-end differentiable systems to model neural networks, stochastic processes, or a game.
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  • 3
    Bridge.jl

    Bridge.jl

    A statistical toolbox for diffusion processes

    Statistics and stochastic calculus for Markov processes in continuous time, include univariate and multivariate stochastic processes such as stochastic differential equations or diffusions (SDE's) or Levy processes.
    Downloads: 0 This Week
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  • 4

    Zarja

    Agent-based simulation toolkit

    It is an open source scientific library that is focused on multi-agent simulations on graphs. It prepares basic toolkit for agents, models, timers, graphs, nodes and edges. It is also accompanied with tools for data processing.
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  • 5
    The Neural Process Family

    The Neural Process Family

    This repository contains notebook implementations

    Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. ...
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  • 6
    STochastic Engine for Pathway Simulation
    Stochastic simulator for signaling pathways occuring in biological cells. Handles reaction-diffusion processes in 3D tetrahedral meshes. Please check our new repository: https://github.com/CNS-OIST/STEPS
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  • 7
    The Sim.DiffProc package simulates and estimates diffusion processes and has functions for numerical solution of multidimensional stochastic differential equations.
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  • 8

    Virus QSP Modeling

    C++ and Python code for simulating RNA virus replication

    Stochastic simulation model of poliovirus Sabin-to-Mahoney genetic state transition (C++ code). Models genotypes, virus populations, and quasispecies cloud. Simulates replication error and copy-choice recombination. Various parameters guiding the model are user-specified. Python code post-processes simulation output to produce report files.
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  • 9

    FAUST2

    Formal Abstractions of Uncountable-STate STochastic processes

    FAUST2 is a software tool that generates formal abstractions of (possibly non-deterministic) discrete-time Markov processes (dtMP) defined over uncountable (continuous) state spaces. A dtMP model is specified in MATLAB and abstracted as a finite-state Markov chain or Markov decision processes. The abstraction procedure runs in MATLAB and employs parallel computations and fast manipulations based on vector calculus. The abstract model is formally put in relationship with the concrete dtMP...
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  • 10
    The DetStoch package offers the user two different methods to compute chemical reactions: Deterministic and Stochastic approaches. It allows the user to play with an intuitive GUI framework and compute the evolution rates of the chemical reactions with the different methods available. The results are displayed in graphical plots of the species concentration over the time. The package is designed to solve any of the following reactions by either one of the two approaches...
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  • 11
    SPiM2Eclipse

    SPiM2Eclipse

    Eclipse plugin for Stochastic Pi Machine

    Stochastic Pi Machine (SPiM), created by Microsoft, is a programming language for modeling biological processes. Two tools are available from Microsoft for simulation. A web application Visual SPiM, and a destkop application SPiM Player. Both simulation tools require to be run on a Windows platform. Fortunately Microsoft has also released a command line version for Linux and Mac OS based on OCAML however this version will only output a CSV file for the simulation results. ...
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  • 12

    simbTUM

    Simulation of stochastic processes and ODE models in biology.

    SIMulation of Biological systems (developed at the TU Munich) This program allows to define ODE-models or stochastic compartemental models of biological processes, to simulate, to fit data and to do some statistics (fitting and statistics for deterministic models only).
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  • 13
    Java library for Monte Carlo simulation, stochastic processes, finance. Classes define the basic mathematical notions to ease transition from theory to application.
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  • 14
    T3S Tool

    T3S Tool

    Learning Stochastic Discrete Event Systems

    Stochastic discrete event system analysis and verification are essential in order to ensure reliability in such systems. However, models that cannot be constructed with an hand-made process need to be learned. Thus, the SDES toolbox proposes an automated solution that is embedded in Matlab to learning and analisis generalized semi-Markov processes.
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  • 15
    The Calculus of Wrapped Compartments is a variant of the Calculus of Looping Sequences. CWC strongly simplifies the development of automatic tools for the analysis of biological systems. The SCWC-sim is a OCaml implementation of CWC calculus.
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  • 16
    ...It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.
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  • 17
    KStochastic gives the user the ability to create pictures of stochastic processes based on arbitrary probability distributions. Those pictures can then be used for illustration purposes in various publications treating random phenomena.
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